포지션 소개
-
Strong hands-on AWS Data Engineering experience across large-scale cloud data platforms.
-
Expertise in AWS S3, AWS Glue, AWS Lambda, AWS Redshift, AWS Lake Formation, AWS CloudWatch and AWS IAM.
-
Strong experience in real-time and streaming data processing using Amazon Kinesis Data Streams, Kinesis Firehose, Kinesis Analytics, Amazon Kafka or equivalent streaming technologies.
-
Hands-on coding proficiency in Python, Py Spark and SQL with strong optimization skills.
-
Experience building high-volume, low-latency data ingestion and transformation pipelines.
-
Strong experience in Databricks, Delta Lake, Structured Streaming and Spark Performance Tuning.
-
Experience handling TB/PB-scale datasets, partitioning strategies, file optimization, schema evolution and data lifecycle management.
-
Strong understanding of Data Lake, Lakehouse and Modern Data Platform architectures.
-
Practical data modeling experience for analytical, operational and reporting workloads.
-
Experience implementing CI/CD pipelines using AWS Code Pipeline, Code Build, CodeDeploy, GitHub Actions or Jenkins.
-
Strong troubleshooting skills for production issues, performance bottlenecks and cost optimization.
-
Excellent client communication, stakeholder management and problem-solving skills.
-
Ensure data quality, governance, security, monitoring and production support.
-
Collaborate with architects, stakeholders and cross-functional teams in Agile delivery environments.
-
Troubleshoot and optimize end-to-end AWS data platforms, streaming pipelines and cloud infrastructure
Education: Bachelor of Engineering,Bachelor Of Technology
Preferred skills: Technology->Cloud->AWS,Technology->Cloud->AWS Core services,Technology->Cloud->AWS - Database Technologies
